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[X=left| egin{matrix} x_{11} & x_{12} & cdots & x_{1d}\ x_{21} & x_{22} & cdots & x_{2d}\ vdots & vdots & ddots & vdots \ x_{11} & x_{12} & cdots & x_{1d}\ end{matrix} ight| ]

[egin{matrix} 1 & x & x^2\ 1 & y & y^2\ 1 & z & z^2\ end{matrix} ]

[left{ egin{array}{c} a_1x+b_1y+c_1z=d_1\ a_2x+b_2y+c_2z=d_2\ a_3x+b_3y+c_3z=d_3 end{array} ight} ]

[X=egin{pmatrix} 0&1&1\ 1&1&0\ 1&0&1\ end{pmatrix} ]

1. 希腊字母表

Sigma: (Sigma)

2. 上下标、根号、省略号

  • 下标:_ x^2 (Longrightarrow) $ x^2$

  • 上标:^ x_i(Longrightarrow) (x_i)

  • 根号:sqrt | ysqrt{x}(Longrightarrow) (ysqrt{x})

  • 省略号:

    dots (Longrightarrowdots)

    cdots (Longrightarrowcdots)

    ddots (Longrightarrowddots)

  • 括号

3. 运算符

  • 求和: sum_1^n(Longrightarrow) (sum_1^n)
  • 积分:int_1^n (Longrightarrow) (int_1^n)
  • 极限:lim_{x o infty}(Longrightarrow) (lim_{x o infty})
  • 分数:frac{2}{3} (Longrightarrow) $frac{2}{3} $

4. 箭头

leftarrow对应 (leftarrow)

5. 分段函数

f(n)=
	egin{cases}
		n/2, & 	ext{if $n$ is even}\
		3n+1,& 	ext{if $n$ is odd}
	end{cases}

[f(n)= egin{cases} n/2, & ext{if $n$ is even}\ 3n+1,& ext{if $n$ is odd} end{cases} ]

6. 方程组

left.
  left{
    egin{array}{c}
      a_1x+b_1y+c_1z=d_1\
      a_2x+b_2y+c_2z=d_2\
      a_3x+b_3y+c_3z=d_3
    end{array}
  
ight.
  
ight>

[left. left{ egin{array}{c} a_1x+b_1y+c_1z=d_1\ a_2x+b_2y+c_2z=d_2\ a_3x+b_3y+c_3z=d_3 end{array} ight. ight> ]

7.矩阵

7.1 基本语法

  • 起始标记 egin{matrix},结束标记 end{matrix}
  • 每一行末尾标记 \
  • 行间元素之间用 & 分隔。
egin{matrix}
0&1&1\
1&1&0\
1&0&1\
end{matrix}

[egin{matrix} 0&1&1\ 1&1&0\ 1&0&1\ end{matrix} ]

7.2 矩阵边框

  • 在起始、结束标记用下列词替换 matrix
  • pmatrix:小括号边框
  • bmatrix:中括号边框
  • Bmatrix:大括号边框
  • vmatrix:单竖线边框
  • Vmatrix:双竖线边框
egin{vmatrix}
0&1&1\
1&1&0\
1&0&1\
end{vmatrix}

[egin{vmatrix} 0&1&1\ 1&1&0\ 1&0&1\ end{vmatrix} ]

7.3 省略元素

  • 横省略号:cdots
  • 竖省略号:vdots
  • 斜省略号:ddots
egin{bmatrix}
{a_{11}}&{a_{12}}&{cdots}&{a_{1n}}\
{a_{21}}&{a_{22}}&{cdots}&{a_{2n}}\
{vdots}&{vdots}&{ddots}&{vdots}\
{a_{m1}}&{a_{m2}}&{cdots}&{a_{mn}}\
end{bmatrix}

[egin{bmatrix} {a_{11}}&{a_{12}}&{cdots}&{a_{1n}}\ {a_{21}}&{a_{22}}&{cdots}&{a_{2n}}\ {vdots}&{vdots}&{ddots}&{vdots}\ {a_{m1}}&{a_{m2}}&{cdots}&{a_{mn}}\ end{bmatrix} ]

7.4 阵列

  • 需要array环境:起始、结束处以{array}声明
  • 对齐方式:在{array}后以{}逐行统一声明
  • 左对齐:l 居中:c 右对齐:r
  • 竖直线:在声明对齐方式时,插入 | 建立竖直线
  • 插入水平线:hline
egin{array}{c|lll}
{↓}&{a}&{b}&{c}\
hline
{R_1}&{c}&{b}&{a}\
{R_2}&{b}&{c}&{c}\
end{array}

[egin{array}{c|lll} {↓}&{a}&{b}&{c}\ hline {R_1}&{c}&{b}&{a}\ {R_2}&{b}&{c}&{c}\ end{array} ]

  • 需要array环境:起始、结束处以{array}声明

7.5 等号上下文字

arrowname[sub-script]{super-script}
  • arrowname具体见下面,等号名称
  • sub-script 代表等号下面内容
  • super-script 代表等号上面内容

8.常用公式

8.1 线性模型

h(	heta) = sum_{j=0} ^n 	heta_j x_j

[h( heta) = sum_{j=0} ^n heta_j x_j ]

8.2 均方误差

J(	heta) = frac{1}{2m}sum_{i=0}^m(y^i - h_	heta(x^i))^2

[J( heta) = frac{1}{2m}sum_{i=0}^m(y^i - h_ heta(x^i))^2 ]

8.3 求积

H_c=sum_{l_1+dots +l_p}prod^p_{i=1} inom{n_i}{l_i}

[H_c=sum_{l_1+dots +l_p}prod^p_{i=1} inom{n_i}{l_i} ]

8.4 批梯度下降

egin{align}
	frac{partial J(	heta)}{partial	heta_j}
	& = -frac1msum_{i=0}^m(y^i - h_	heta(x^i)) frac{partial}{partial	heta_j}(y^i-h_	heta(x^i))\
	& = -frac1msum_{i=0}^m(y^i-h_	heta(x^i)) frac{partial}{partial	heta_j}(sum_{j=0}^n	heta_j x^i_j-y^i)\
	&=-frac1msum_{i=0}^m(y^i -h_	heta(x^i)) x^i_j
end{align}

[frac{partial J( heta)}{partial heta_j} = -frac1msum_{i=0}^m(y^i - h_ heta(x^i))x^i_j ]

[egin{align} frac{partial J( heta)}{partial heta_j} & = -frac1msum_{i=0}^m(y^i - h_ heta(x^i)) frac{partial}{partial heta_j}(y^i-h_ heta(x^i))\ & = -frac1msum_{i=0}^m(y^i-h_ heta(x^i)) frac{partial}{partial heta_j}(sum_{j=0}^n heta_j x^i_j-y^i)\ &=-frac1msum_{i=0}^m(y^i -h_ heta(x^i)) x^i_j end{align} ]


引用

原文地址:https://www.cnblogs.com/geoffreyone/p/14992044.html